--- title: "Execute Vision Model Endpoint" url: https://docs.catalyst.zoho.com/en/sdk/javascript/v1/quickml/execute-vision-model-endpoint/ description: "This page describes the method to perform operations using the components in SmartBrowz Services." last_updated: 2026-09-23T13:11:30Z service: QuickML type: general related_links: - name: "Catalyst QuickML" url: /en/quickml/ - name: "Java SDK Documentation" url: /en/sdk/java/v1/quickml/execute-quickml-endpoints/ - name: "NodeJS SDK Documentation" url: /en/sdk/nodejs/v2/quickml/execute-quickml-endpoints/ - name: "Python SDK Documentation" url: /en/sdk/python/v1/pipelines/execute-pipeline/ - name: "REST API Documentation" url: /en/api/code-reference/pipelines/execute-pipeline/#ExecutePipeline --- ## Vision Language Model ## QuickML hosts Vision Language Models in the LLM Serving module under the Generative AI section in the console. VLMs are multimodal models that accept a file object along with a text prompt and return a natural language response. The model interprets the image according to the text prompt instruction and generates an appropriate response. Interaction with Vision Language Model works similar to single shot interaction mode with LLM. Each request must carry its own file and prompt and is processed independently, with no memory of previous requests. To analyze the same image again with a different instruction, send a new request. **Execute Vision Model Endpoint** VLM is served with its own set of parameters, giving you control over the response before publishing it. You can test a model with sample images and prompts in the test interface, save the configuration, and create an endpoint from it to integrate with your application. A Vision Model endpoint is created from a saved parameter configuration, so the model, system prompt, instructions, and generation parameters you tested in the console are exactly what your application calls. The endpoint must be created from a configuration that uses a Vision Language Model, text-only LLM endpoints do not accept image input. Open the image in binary read mode and pass the file object to the method. > **Note:** 1. You will need to have the Vision Language Model endpoint created and published in your project using the Catalyst console, before you execute the code snippet below. 2. QuickML is currently available to Catalyst users accessing from the US, IN, and EU data centes. ### a. Analyze an Image The **analyzeImage(imageEndpointKey, imageBase64, imagePrompt)** method requires the endpoint key, a Base64-encoded image, and an input prompt. The endpoint key is generated when the VLM endpoint is created. This method sends an image and an accompanying prompt to a published Vision Language Model (VLM) endpoint and returns the model's response. **Parameters used**
| Parameter | Description | Values |
|---|---|---|
| imageEndpointKey | The unique ID of the VLM endpoint published in your project | String |
| imageBase64 | The Base64-encoded image to be analyzed. | String |
| imagePrompt | The task the model must perform on the image | String |